Search Results for author:
Found 3 papers, 0 papers with code
Motion Flow Matching for Human Motion Synthesis and Editing
In this paper, we propose \emph{Motion Flow Matching}, a novel generative model designed for human motion generation featuring efficient sampling and effectiveness in motion editing applications.
Learning Context-Adapted Video-Text Retrieval by Attending to User Comments
Learning strong representations for multi-modal retrieval is an important problem for many applications, such as recommendation and search.
Measuring the Interpretability of Unsupervised Representations via Quantized Reversed Probing
Self-supervised visual representation learning has attracted significant research interest.
Ranked #90 on
Image Classification
on ObjectNet
(using extra training data)
